Many researchers have been focused on improving the performance of the buddy system via a hardware implementation, but that does not improve performance drastically. This thesis presents three all size sets hardware-assisted memory allocators (HAMAs) based on Chang’s or-gate tree to eliminate the size blind spot in the buddy system. Our HAMAs can allocate a free memory block of any size in the system. This effectively eliminates external fragmentation. We use SPECjvm98 benchmark to collect the information of object allocation and de-allocation and then exploit this information to test our HAMAs and others. The results of simulation indicate that our all size HAMA uses less memory space and effectively improve memory utilization.